Automation and Editorial Judgment: Assessing AI’s Influence on News Production in the Digital Era

Abstract

The study investigates the mechanisms through which artificial intelligence reconfigures editorial judgment and the institutional core of news production. Rapid algorithmic integration into newsroom workflows remains a central driver of this shift, deepening the dependence of journalism on platform infrastructures. Rather than treating AI as a neutral aid, the work conceptualizes it as a structural force recalibrating gatekeeping, labor relations, and epistemic authority. The analysis traces the transition from human-centered models to hybrid algorithmic gatekeeping, examining how metric-driven decision-making impacts autonomy and professional identity. Particular attention is paid to algorithmic and labor asymmetries in the Global South. The inquiry concludes by addressing the necessity of critical AI literacy and institutional governance to mitigate these automated power shifts. The work describes the transition from human-centered gatekeeping to hybrid and algorithmic models, analyzes the emergence of metric-driven decision-making, and studies the consequences of automation for journalistic autonomy and professional identity. Special attention is paid to the unequal geography of AI adoption, with a focus on the Global South and the phenomenon of algorithmic and labor asymmetries. The article sets itself the goal of systematizing the mechanisms through which AI influences editorial decisions and newsroom power structures. Comparative analysis, source analysis, and conceptual synthesis are used to solve this task. The conclusion describes the need for critical AI literacy and institutional governance of automated systems. The article will be useful for researchers in journalism studies, media sociology, and communication policy.